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Education

• Ph.D., Biology, Harvard University (2020)
• Masters of Arts, Biology, Harvard University (2016)
• Bachelors of Science, Biochemistry and Molecular Biology, Michigan State University (2014)

Research Interests

My research crosses a few disciplines, from ecology and pollinator biology to behavioral neuroscience. A core question I focus on is how do ecological stressors impact the behavior of insects (like bumblebees) which play critical roles in the global ecosystem. And how does natural variation in sensory perception create variability in responses to these stressors on individual and colony wide levels.

Awards

• Genes in Space Hatch Prize for Mentorship (2022)
• GoogleX AI Resident (2020)
• Harvard Quantitative Student Fellow (2019–2020)

Projects

A recent project that I’ve been working on has been trying to design better methods for tracking insects in natural settings. One of the challenges in this field are that insects are abundant, small and can move quite quickly. Tracking insects is important for many different reasons: pests in agriculture, ticks or mosquitos for human health, pollinators for conservation/food supply. This necessitates a tool that can densely monitor populations and do this over longer periods of time. Our solution was to create an open source, field deployable, autonomous camera trap designed for detecting and classifying insects visiting flowers. The camera trap uses an object detection model trained on insects to filter data to increase signal to noise in the final output dataset, saving storage space and hours of sorting through data. I hope this tool can be useful to other researchers in the field as well as even hobbyists interested in tracking who is visiting their garden!